A Novel Framework for Object-Based Coding and Compression of Hyperspectral Imagery

被引：0

作者：

ZHAO Chunhui ^{[1
]}

LI Xiaohui ^{[1
,2
]}

REN Jinchang ^{[2
]}

Stephen Marshall ^{[2
]}

机构：

[1] College of Information and Communication Engineering, Harbin Engineering University

[2] Department of Electronic and Electrical Engineering, University of Strathclyde

来源：

ChineseJournalofElectronics | 2015年 / 24卷 / 02期

基金：

中国国家自然科学基金; 中央高校基本科研业务费专项资金资助;

关键词：

Hyperspectral imagery(HSI); Objectbased image compression; Sparse representation; Target detection; Remote sensing;

D O I：

暂无

中图分类号：

TP391.41 [];

学科分类号：

080203 ;

摘要：

A novel object-based framework is proposed for HSI compression, where targets of interest are extracted and separately coded. With objects removed,the holes are filled with the background average to form a new but more homogenous background for better compression. An improved sparse representation with adaptive spatial support is proposed for target detection. By applying the proposed framework to 2D/3D DCT approaches,reconstructed images from conventional and proposed approaches are compared. Six criteria in three groups are employed for quantitative evaluations to measure the degree of data reduction, the distortion of reconstructed image quality and accuracy in target detection, respectively. Comprehensive experiments on two datasets are used for performance evaluation. It is found that the proposed approaches yield much improved results.

引用

页码：300 / 305

页数：6

共 15 条

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